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tf.keras.callbacks.LearningRateScheduler

TensorFlow 1 version View source on GitHub

Class LearningRateScheduler

Learning rate scheduler.

Inherits From: Callback

Used in the tutorials:

Arguments:

  • schedule: a function that takes an epoch index as input (integer, indexed from 0) and returns a new learning rate as output (float).
  • verbose: int. 0: quiet, 1: update messages.
# This function keeps the learning rate at 0.001 for the first ten epochs
# and decreases it exponentially after that.
def scheduler(epoch):
  if epoch < 10:
    return 0.001
  else:
    return 0.001 * tf.math.exp(0.1 * (10 - epoch))

callback = tf.keras.callbacks.LearningRateScheduler(scheduler)
model.fit(data, labels, epochs=100, callbacks=[callback],
          validation_data=(val_data, val_labels))

__init__

View source

__init__(
    schedule,
    verbose=0
)

Initialize self. See help(type(self)) for accurate signature.

Methods

set_model

View source

set_model(model)

set_params

View source

set_params(params)

Compat aliases